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Pseudo-Dolly-In Video Generation Combining 3D Modeling and Image Reconstruction

机译:结合3D建模和图像重建的伪多莉输入视频生成

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This paper proposes a pseudo-dolly-in video generation method that reproduces motion parallax by applying image reconstruction processing to multi-view videos. Since dolly-in video is taken by moving a camera forward to reproduce motion parallax, we can present a sense of immersion. However, at a sporting event in a large-scale space, moving a camera is difficult. Our research generates dolly-in video from multi-view images captured by fixed cameras. By applying the Image-Based Modeling technique, dolly-in video can be generated. Unfortunately, the video quality is often damaged by the 3D estimation error. On the other hand, Bullet-Time realizes high-quality video observation. However, moving the virtual-viewpoint from the capturing positions is difficult. To solve these problems, we propose a method to generate a pseudo-dolly-in image by installing 3D estimation and image reconstruction techniques into Bullet-Time and show its effectiveness by applying it to multi-view videos captured at an actual soccer stadium. In the experiment, we compared the proposed method with digital zoom images and with the dolly-in video generated from the Image-Based Modeling and Rendering method.
机译:本文提出了一种通过将图像重构处理应用于多视点视频来再现运动视差的伪多点输入视频生成方法。由于向前移动摄像机来拍摄多莉摄录视频,以重现运动视差,因此我们可以呈现沉浸感。然而,在大型空间中的体育比赛中,移动照相机是困难的。我们的研究从固定摄像机捕获的多视图图像中生成多莉视频。通过应用基于图像的建模技术,可以生成移动式视频。不幸的是,视频质量通常会因3D估计误差而受损。另一方面,Bullet-Time实现了高质量的视频观察。然而,从捕获位置移动虚拟视点是困难的。为了解决这些问题,我们提出了一种通过在Bullet-Time中安装3D估计和图像重建技术来生成伪造的动态图像的方法,并通过将其应用于实际足球场中捕获的多视图视频来显示其有效性。在实验中,我们将提出的方法与数字缩放图像以及从基于图像的建模和渲染方法生成的多莉视频进行了比较。

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